This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. High-density surface coil arrays have been used for attaining highly-accelerated, high resolution images for brain, breast and cardiac MRI studies [1,2]. Due to the layout and size of the coil elements, these arrays usually exhibit sensitivity variations across the field of view. Several intensity correction schemes have been investigated in literature, and many of these algorithms significantly change the spatial noise profile during the process, which is undesirable [3,4]. In this study, we present a variable voxel-size intensity correction method that maintains the original noise profile while reducing intensity variations across the image. The principle idea consists of averaging voxels in regions of low sensitivity and properly scaling the result, thereby boosting the SNR in these regions. We present the results of this variable voxel-size algorithm for an ultrahigh resolution, 3D breast patient scan using a 16-channel surface coil array. We assumed that the coil intensity profile is a slowly varying spatial function and approximated this bias field using a low pass filter on the original data. We normalized this bias field and created a "voxel volume" map where larger voxel sizes correspond to regions of low intensity of the bias field. We passed the original dataset individually through scaled low pass filters of varying bandwidths to achieve the desired resolution in the voxel volume map. In the final corrected dataset, we chose the appropriate dataset for each voxel based on the voxel volume map. To read about other projects ongoing at the Lucas Center, please visit http://rsl.stanford.edu/ (Lucas Annual Report and ISMRM 2011 Abstracts)